get negative from prod(x) when x is positive integers using python

Question

I have a list of a list of integers. The lists are long so i cant really show an actual example of on of the lists, but I know that they contain only the integers 1,2,3,4.

so for example. s2 = [[1,2,2,3,2,1,4,4],[2,4,3,2,3,1]]

I am calculating the product, sum, max, min.... of each list in s2 but I get negative or 0 for the product for a lot of the lists. (I am doing this in ipython)

for x in s2: Â  Â  print(len = , len(x), sum = , sum(x), prod = , prod(x), max = , max(x), min = , min(x))
...
 (len = , 100, sum = , 247, prod = , 0, max = , 4, min = , 1) (len = , 100, sum = , 230, prod = , -4611686018427387904, max = , 4, min = , 1) (len = , 100, sum = , 261, prod = , 0, max = , 4, min = , 1)
 .....
 (prod =, 0, max =, 4, min =, 1) (prod =, 1729382256910270464, max =, 4, min =, 1) (prod =, 0, max =, 4, min =, 1)
.... 

Whats going on?

Answer 1

Instead of Python's integer type (int/long) numpy uses the faster machine
integers (typically 32 or 64 bit) that overflow:

>>> a = numpy.array([0xffffffff, 0xffffffff])
>>> numpy.prod(a)
-**********
>>> a.dtype
dtype('int64')

As a workaround you can use Python's ints (slower)

>>> a = numpy.array([0xffffffff, 0xffffffff], dtype=object)
>>> numpy.prod(a)
18446744065119617025L

or float (loss of precision)

>>> a = numpy.array([0xffffffff, 0xffffffff], dtype=float)
>>> numpy.prod(a)
1.8446744065119617e+19